Result: Elimination AD applied to Jacobian assembly for an implicit compressible CFD solver

Title:
Elimination AD applied to Jacobian assembly for an implicit compressible CFD solver
Authors:
TADJOUDDINE, Mohamed, FORTH, Shaun A, NING QIN
Source:
8th ICFD Conference on Numerical Methods for Fluid Dynamics: Part 2International journal for numerical methods in fluids. 47(10-11):1315-1321
Publisher Information:
Chichester: Wiley, 2005.
Publication Year:
2005
Physical Description:
print, 15 ref
Original Material:
INIST-CNRS
Subject Terms:
Mechanics acoustics, Mécanique et acoustique, Sciences exactes et technologie, Exact sciences and technology, Physique, Physics, Domaines classiques de la physique (y compris les applications), Fundamental areas of phenomenology (including applications), Mécanique des fluides, Fluid dynamics, Méthodes de calcul en mécanique des fluides, Computational methods in fluid dynamics, Algorithme, Algorithms, Dérivation mathématique, Differentiation, Fluide compressible, Compressible fluid, Fluido compresible, Mécanique fluide numérique, Computational fluid dynamics, Méthode Newton, Newton method, Méthode itérative, Iterative methods, Préconditionnement, Preconditioning, Precondicionamiento, Simulation numérique, Digital simulation, Newton solver, PNS, algorithmic differentiation, vertex elimination algorithm
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Engineering Systems Department, Cranfield University (Shrivenham Campus), ESD AMOR Group, Swindon SN68LA, United Kingdom
Department of Mechanical Engineering, The University of Sheffield, Mappin Street, S1 3JD, United Kingdom
ISSN:
0271-2091
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=16684421
Rights:
Copyright 2005 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Physics: fluid mechanics
Accession Number:
edscal.16684421
Database:
PASCAL Archive

Further Information

In CFD, Newton solvers have the attractive property of quadratic convergence but they require derivative information. An efficient way of computing derivatives is by algorithmic differentiation (AD) also known as automatic differentiation or computational differentiation. AD allows us to evaluate derivatives, usually at a cheap cost, without the truncation errors associated with finite-differencing. Recently, efficient and reliable AD tools for evaluating derivatives have been published. In this paper, we use some of the best AD tools currently available to build up the system Jacobian involved in the solution of a finite-volume parabolized Navier-Stokes (PNS) solver. Our aim is to direct scientists and engineers confronted with the calculation of derivatives to the use of AD and to highlight those AD tools that they should try. Moreover, we introduce an AD tool that produces Jacobian code that runs usually twice as fast as that from conventional AD tools.